{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T08:20:32Z","timestamp":1743063632775,"version":"3.40.3"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319479545"},{"type":"electronic","value":"9783319479552"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-3-319-47955-2_26","type":"book-chapter","created":{"date-parts":[[2016,10,13]],"date-time":"2016-10-13T15:04:10Z","timestamp":1476371050000},"page":"310-322","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["In Defense of Online Kmeans for Prototype Generation and Instance Reduction"],"prefix":"10.1007","author":[{"given":"Mauricio","family":"Garc\u00eda-Lim\u00f3n","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hugo Jair","family":"Escalante","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alicia","family":"Morales-Reyes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,10,14]]},"reference":[{"issue":"1","key":"26_CR1","first-page":"37","volume":"6","author":"DW Aha","year":"1991","unstructured":"Aha, D.W., Kibler, D., Albert, M.: Instance-based learning algorithms. Mach. Learn. 6(1), 37\u201366 (1991)","journal-title":"Mach. Learn."},{"issue":"11","key":"26_CR2","doi-asserted-by":"publisher","first-page":"1450","DOI":"10.1109\/TKDE.2007.190645","volume":"19","author":"F Angiulli","year":"2007","unstructured":"Angiulli, F.: Fast nearest neighbor condensation for large data sets classification. IEEE Trans. Knowl. Data Eng. 19(11), 1450\u20131464 (2007)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"26_CR3","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/j.knosys.2016.05.056","volume":"107","author":"A Arnaiz","year":"2016","unstructured":"Arnaiz, A., Diez, F., Rodrguez, J.J., Garca, C.: Instance selection of linear complexity for big data. Knowl.-Based Syst. 107, 83\u201395 (2016)","journal-title":"Knowl.-Based Syst."},{"key":"26_CR4","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1007\/978-3-540-28650-9_7","volume-title":"Advanced Lectures on Machine Learning","author":"L Bottou","year":"2004","unstructured":"Bottou, L.: Stochastic learning. In: Bousquet, O., von Luxburg, U., R\u00e4tsch, G. (eds.) Machine Learning 2003. LNCS (LNAI), vol. 3176, pp. 146\u2013168. Springer, Heidelberg (2004)"},{"issue":"7","key":"26_CR5","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1016\/j.patrec.2004.09.043","volume":"26","author":"JR Cano","year":"2005","unstructured":"Cano, J.R., Herrera, F., Lozano, M.: Stratification for scaling up evolutionary prototype selection. Pattern Recogn. Lett. 26(7), 953\u2013963 (2005)","journal-title":"Pattern Recogn. Lett."},{"issue":"1","key":"26_CR6","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","volume":"13","author":"TM Cover","year":"1967","unstructured":"Cover, T.M., Hart, P.E.: Nearest neighbor pattern classification. IEEE Trans. Inf. Theor. 13(1), 21\u201327 (1967)","journal-title":"IEEE Trans. Inf. Theor."},{"key":"26_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1007\/978-3-319-19264-2_6","volume-title":"MCPR 2015","author":"I Cruz-Vega","year":"2015","unstructured":"Cruz-Vega, I., Escalante, H.J.: Improved learning rule for LVQ based on granular computing. In: Carrasco-Ochoa, J.A., Mart\u00ednez-Trinidad, J.F., Sossa-Azuela, J.H., Olvera L\u00f3pez, J.A., Famili, F. (eds.) MCPR 2015. LNCS, pp. 54\u201363. Springer, Heidelberg (2015)"},{"key":"26_CR8","doi-asserted-by":"crossref","unstructured":"Cruz-Vega, I., Escalante, H.J.: An online and incremental GRLVQ algorithm for prototype generation based on granular computing. Soft Comput. 1\u201314 (2016)","DOI":"10.1007\/s00500-016-2042-0"},{"issue":"3","key":"26_CR9","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1109\/TPAMI.2011.142","volume":"34","author":"S Garcia","year":"2012","unstructured":"Garcia, S., Derrac, J., Cano, J., Herrera, F.: Prototype selection for nearest neighbor classification: taxonomy and empirical study. IEEE Trans. Pattern Anal. Mach. Intell. 34(3), 417\u2013435 (2012)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"26_CR10","doi-asserted-by":"crossref","unstructured":"Garc\u00eda-Lim\u00f3n, M., Escalante, H.J., Morales, E., Morales-Reyes, A.: Simultaneous generation of prototypes and features through genetic programming. In: Proceedings of the Conference on Genetic and Evolutionary Computation, pp. 517\u2013524. ACM (2014)","DOI":"10.1145\/2576768.2598356"},{"key":"26_CR11","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1016\/j.ins.2012.10.006","volume":"228","author":"N Garcia-Pedrajas","year":"2013","unstructured":"Garcia-Pedrajas, N., de Haro-Garcia, A., Perez-Rodriguez, J.: A scalable approach to simultaneous evolutionary instance and feature selection. Inf. Sci. 228, 150\u2013174 (2013)","journal-title":"Inf. Sci."},{"issue":"3","key":"26_CR12","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1109\/TIT.1968.1054155","volume":"14","author":"P Hart","year":"1968","unstructured":"Hart, P.: The condensed nearest neighbor rule (corresp.). IEEE Trans. Inf. Theor. 14(3), 515\u2013516 (1968)","journal-title":"IEEE Trans. Inf. Theor."},{"key":"26_CR13","series-title":"Springer Series in Statistics","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-21606-5","volume-title":"The Elements of Statistical Learning","author":"T Hastie","year":"2001","unstructured":"Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning. Springer Series in Statistics. Springer, New York (2001)"},{"issue":"1","key":"26_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/S0925-2312(98)00030-7","volume":"21","author":"T Kohonen","year":"1998","unstructured":"Kohonen, T.: The self-organizing map. Neurocomputing 21(1), 1\u20136 (1998)","journal-title":"Neurocomputing"},{"issue":"11\u201313","key":"26_CR15","doi-asserted-by":"publisher","first-page":"1149","DOI":"10.1016\/S0167-8655(99)00082-3","volume":"20","author":"LI Kuncheva","year":"1999","unstructured":"Kuncheva, L.I., Jain, L.C.: Nearest neighbor classifier: simultaneous editing and feature selection. Pattern Recogn. Lett. 20(11\u201313), 1149\u20131156 (1999)","journal-title":"Pattern Recogn. Lett."},{"key":"26_CR16","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1007\/978-3-319-17551-5_4","volume-title":"Business Intelligence","author":"V Lemaire","year":"2015","unstructured":"Lemaire, V., Salperwyck, C., Bondu, A.: A survey on supervised classification on data streams. In: Zim\u00e1nyi, E., Kutsche, R.-D. (eds.) eBISS 2014. LNBIP, vol. 205, pp. 88\u2013125. Springer, Heidelberg (2015)"},{"issue":"4","key":"26_CR17","doi-asserted-by":"publisher","first-page":"1092","DOI":"10.1016\/j.neucom.2008.03.008","volume":"72","author":"L Nanni","year":"2009","unstructured":"Nanni, L., Lumini, A.: Particle swarm optimization for prototype reduction. Neurocomputing 72(4), 1092\u20131097 (2009)","journal-title":"Neurocomputing"},{"issue":"2","key":"26_CR18","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1007\/s10044-008-0142-x","volume":"13","author":"JA Olvera-L\u00f3pez","year":"2010","unstructured":"Olvera-L\u00f3pez, J.A., Carrasco-Ochoa, J.A., Mart\u00ednez-Trinidad, J.F.: A new fast prototype selection method based on clustering. Pattern Anal. Appl. 13(2), 131\u2013141 (2010)","journal-title":"Pattern Anal. Appl."},{"key":"26_CR19","first-page":"1","volume":"19","author":"S Ougiaroglou","year":"2014","unstructured":"Ougiaroglou, S., Evangelidis, G.: RHC: a non-parametric cluster-based data reduction for efficient k-NN classification. Pattern Anal. Appl. 19, 1\u201317 (2014)","journal-title":"Pattern Anal. Appl."},{"issue":"10","key":"26_CR20","doi-asserted-by":"publisher","first-page":"1554","DOI":"10.1016\/j.patrec.2005.01.003","volume":"26","author":"T Raicharoen","year":"2005","unstructured":"Raicharoen, T., Lursinsap, C.: A divide-and-conquer approach to the pairwise opposite class-nearest neighbor (POC-NN) algorithm. Pattern Recogn. Lett. 26(10), 1554\u20131567 (2005)","journal-title":"Pattern Recogn. Lett."},{"issue":"6","key":"26_CR21","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1016\/S0167-8655(97)00035-4","volume":"18","author":"JS S\u00e1nchez","year":"1997","unstructured":"S\u00e1nchez, J.S., Pla, F., Ferri, F.: Prototype selection for the nearest neighbour rule through proximity graphs. Pattern Recogn. Lett. 18(6), 507\u2013513 (1997)","journal-title":"Pattern Recogn. Lett."},{"key":"26_CR22","first-page":"225","volume":"113","author":"M Lozano","year":"2004","unstructured":"Lozano, M., Sotoca, J.M., Sanchez, J.S., Pla, F.: An adaptive condensing algorithm based on mixtures of gaussians. Recent Adv. Artif. Intell. Res. Dev. 113, 225 (2004)","journal-title":"Recent Adv. Artif. Intell. Res. Dev."},{"key":"26_CR23","unstructured":"Toussaint, G.T.: Proximity graphs for nearest neighbor decision rules: recent progress. In: Interface-2002, 34th Symposium on Computing and Statistics (2002)"},{"issue":"1","key":"26_CR24","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1109\/TSMCC.2010.2103939","volume":"42","author":"I Triguero","year":"2012","unstructured":"Triguero, I., Derrac, J., Garcia, S., Herrera, F.: A taxonomy and experimental study on prototype generation for nearest neighbor classification. Trans. Syst. Man Cybern. Part C 42(1), 86\u2013100 (2012)","journal-title":"Trans. Syst. Man Cybern. Part C"},{"key":"26_CR25","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1016\/j.neucom.2014.04.078","volume":"150","author":"I Triguero","year":"2015","unstructured":"Triguero, I., Peralta, D., Bacardit, J., Garc\u00eda, S., Herrera, F.: MRPR: a mapreduce solution for prototype reduction in big data classification. Neurocomputing 150, 331\u2013345 (2015). Part A","journal-title":"Neurocomputing"},{"issue":"3","key":"26_CR26","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1023\/A:1007626913721","volume":"38","author":"DR Wilson","year":"2000","unstructured":"Wilson, D.R., Martinez, T.: Reduction techniques for instance-based learning algorithms. Mach. Learn. 38(3), 257\u2013286 (2000)","journal-title":"Mach. Learn."},{"key":"26_CR27","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1109\/TSMC.1972.4309137","volume":"3","author":"DL Wilson","year":"1972","unstructured":"Wilson, D.L.: Asymptotic properties of nearest neighbor rules using edited data. IEEE Trans. Syst. Man Cybern. 3, 408\u2013421 (1972)","journal-title":"IEEE Trans. Syst. Man Cybern."},{"issue":"1","key":"26_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10115-007-0114-2","volume":"14","author":"X Wu","year":"2007","unstructured":"Wu, X., Kumar, V., Quinlan, R., Ghosh, J., Yang, Q., Motoda, H., McLachlan, G., Ng, A., Liu, B., Yu, P., Zhou, Z., Steinbach, M., Hand, D., Steinberg, D.: Top 10 algorithms in data mining. Knowl. Inf. Syst. 14(1), 1\u201337 (2007)","journal-title":"Knowl. Inf. Syst."}],"container-title":["Lecture Notes in Computer Science","Advances in Artificial Intelligence - IBERAMIA 2016"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-47955-2_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T16:58:32Z","timestamp":1710262712000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-47955-2_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319479545","9783319479552"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-47955-2_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2016]]},"assertion":[{"value":"14 October 2016","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IBERAMIA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ibero-American Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"San Jos\u00e9","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Costa Rica","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2016","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 November 2016","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 November 2016","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iberamia2016","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}